Data Scientist

Role and Responsibilities

• Own the product analytics of bidgely’s end user-facing products, measure and identify areas of improvement through data
• Liaise with Product Managers and Business Leaders to understand the product issues, priorities and hence support them through relevant product analytics
• Own the automation of product analytics through good SQL knowledge
• Develop early warning metrics for production and highlight issues and breakdowns for resolution
• Resolve client escalations and concerns regarding key business metrics
• Define and own execution
• Own the Energy Efficiency program designs, dashboard development, and monitoring of existing Energy efficiency program
• Deliver data-backed analysis and statistically proven solutions
• Research and implement best practices
• Mentor team of analysts

Qualifications and Education Requirements

• B.Tech from a premier institute with 5+ years analytics experience or Full-time MBA from a premier b-school with 3+ years of experience in analytics/business or product analytics
• Bachelor's degree in Business, Computer Science, Computer Information Systems, Engineering, Mathematics, or other business/analytical disciplines

Skills needed to excel

• Proven analytical and quantitative skills and an ability to use data and metrics to back up assumptions, develop business cases, and complete root cause
  analyses
• Excellent understanding of retention, churn, and acquisition of user base
• Ability to employ statistics and anomaly detection techniques for data-driven
  analytics
• Ability to put yourself in the shoes of the end customer and understand what
  “product excellence” means
• Ability to rethink existing products and use analytics to identify new features and product improvements.
• Ability to rethink existing processes and design new processes for more effective analyses
• Strong SQL knowledge, working experience with Looker and Tableau a great plus
• Strong commitment to quality visible in the thoroughness of analysis and techniques employed
• Strong project management and leadership skills
• Excellent communication (oral and written) and interpersonal skills and an ability to effectively communicate with both business and technical teams
• Ability to coach and mentor analysts on technical and analytical skills
• Good knowledge of statistics, basic machine learning, and AB Testing is
  preferable
• Experience as a Growth hacker and/or in Product analytics is a big plus

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.

 

Skills:

- 5+ years deploying Machine Learning pipelines in large enterprise production systems.

- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.

 

Roles and Responsibilities:

Deploying ML models into production, and scaling them to serve millions of customers.

Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.

Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.

Provide software design and programming support to projects.

 

 Qualifications & Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.

 

• Required to work individually or as part of a team on data science projects and work closely with lines of business to understand business problems and translate them into identifiable machine learning problems which can be delivered as technical solutions.
• Build quick prototypes to check feasibility and value to the business.
• Design, training, and deploying neural networks for computer vision and machine learning-related problems.
• Perform various complex activities related to statistical/machine learning.
• Coordinate with business teams to provide analytical support for developing, evaluating, implementing, monitoring, and executing models.
• Collaborate with technology teams to deploy the models to production.

 

Key Criteria:

• 2+ years of experience in solving complex business problems using machine learning.
• Understanding and modeling experience in supervised, unsupervised, and deep learning models; hands-on knowledge of data wrangling, data cleaning/ preparation, dimensionality reduction is required.
• Experience in Computer Vision/Image Processing/Pattern Recognition, Machine Learning, Deep Learning, or Artificial Intelligence.
• Understanding of Deep Learning Architectures like InceptionNet, VGGNet, FaceNet, YOLO, SSD, RCNN, MASK Rcnn, ResNet.
• Experience with one or more deep learning frameworks e.g., TensorFlow, PyTorch.
• Knowledge of vector algebra, statistical and probabilistic modeling is desirable.
• Proficiency in programming skills involving Python, C/C++, and Python Data Science Stack (NumPy, SciPy, Pandas, Scikit-learn, Jupyter, IPython).
• Experience working with Amazon SageMaker or Azure ML Studio for deployments is a plus.
• Experience in data visualization software such as Tableau, ELK, etc is a plus.
• Strong analytical, critical thinking, and problem-solving skills.

Qualifications:

• B.E/ B.Tech./ M. E/ M. Tech in Computer Science, Applied Mathematics, Statistics, Data Science, or related Engineering field.
• Minimum 60% in Graduation or Post-Graduation
• Great interpersonal and communication skills

Looking for senior data science researchers.

Basic Qualifications:
∙Bachelors in Computer Science/Mathematics + Research (Machine Learning, Deep Learning, Statistics, Data Mining, Game Theory or core mathematical areas) from Tier1 tech institutes.
∙3+ years of relevant experience in building large scale machine learning or deep learning models and/or systems.
∙1 year or more of experience specifically with deep learning (CNN, RNN, LSTM, RBM etc).
∙Strong working knowledge of deep learning, machine learning, and statistics.
- Deep domain understanding of Personalization, Search and Visual.
∙Strong math skills with statistical modeling / machine learning.
∙Hands-on experience building models with deep learning frameworks like MXNet or Tensorflow.
∙Experience in using Python, statistical/machine learning libs.
∙Ability to think creatively and solve problems.
∙Data presentation skills.

Preferred:
∙MS/ Ph.D. (Machine Learning, Deep Learning, Statistics, Data Mining, Game Theory or core mathematical areas) from IISc and other Top Global Universities.
∙Or, Publications in highly accredited journals (If available, please share links to your published work.).
∙Or, history of scaling ML/Deep learning algorithm at massively large scale.

Role Summary - The position holder will be responsible for supporting various aspects of organization's Analytical & BI activities. As a member of team, candidate will collaborate with a multi-disciplinary team of experts and SMT group on a wide range of problems which will give him opportunities to solve critical business problems by using Analytical & Statistical techniques. Essential/Key Responsibilities - By analyzing data/reports to identify early warning signals (unusual trends, patterns, Process gaps etc.) and proactively providing feedback in order to take corrective actions by finding continuous improvement in process (improvement in performance, reducing cost, technological improvement etc.) - Will also be responsible for creating/defining BI (Business Intelligence) and AI (Analytical Intelligence) standards for Home Credit - Being a part of BICC team, expecting high level of Business Intelligence support (Regular Reports, weekly presentations etc.) to top management - Will ensure automation & centralization of BI activities for better utilization of resources - Will be responsible for supporting data driven ADHOC's & critical requirements Qualifications/Requirements: - MBA/ M. Tech / B-Tech or Bachelors in a quantitative discipline such as Computer Science, Engineering, Mathematics, Statistics, Operations Research, Economics from premier /Tier 1 Colleges with a minimum of 3 years of experience in Analytics/ Business Intelligence - Highly numerate/ Statistical knowledge - able to work with numbers and can understand the data trend - Ability to work with both business and technical communities - Good to know, financial analysis / modeling to support the various teams on specific analysis projects. Skills/ Desired Characteristics - Able to think analytically, use a systematics and logical approach to analyze data, problems and situations. - Good Database skills with exposure to Oracle (11g) systems and tools - Highly skilled in Excel, SQL, R/Python or Power BI /Tableau or VBA - Ability to manage multiple deliverables with minimum guidance and pro-actively set up communication processes with stakeholders - Willing to working in IC (Individual Contributor) role - Excellent communication skills in English - written, verbal - Good knowledge in Project Management and Program management. Who should join us - If you are willing to face new challenges and want to apply your data knowledge for growth / future of company, then Home Credit can give you this opportunity. Home Credit can provide you platform to show your skills & suggest valuable ideas to company. - Will get opportunity to work on company level platform & will be part of BI platform of company. - Opportunity to work in a team of enthusiastic professionals.

• B.Tech/MTech from tier 1 institution
• 8+years of experience in machine learning techniques like logistic regression, random forest, boosting, trees, neural networks, etc.
• Showcased experience with Python, SQL and proficiency in Scikit Learn, Pandas, NumPy, Keras and TensorFlow/pytorch
• Experience of working with Qlik sense or Tableau is a plus

Experience of working in a product company is a plus

The Job
The Architect, Machine Learning and Artificial Intelligence including Computer Vision will grow and lead a team of talented Machine Learning (ML), Computer Vision (CV) and Artificial Intelligence (AI) researchers and engineers to develop innovative machine learning algorithms, scalable ML system, and AI applications for Racetrack. This role will be focused on developing and deploying personalization and recommender system, search, experimentation, audience, and content AI solutions to drive user experience and growth.

The Daily

• Develop innovative data science solutions that utilize machine learning and deep learning algorithms, statistical and quantitative modelling approaches to support product, engineering, content, and marketing initiatives.
• Build and lead a world-class team of ML and AI scientists and engineers.
• Be a hands-on leader to mentor the team in latest machine learning and deep learning approaches, and to introduce new technologies and processes. Single headedly manage the MVP and PoCs
• Work with ML engineers to design solution architecture and develop scalable machine learning system to accelerate learning cycle.
• Identify data science opportunities that deliver business value.
• Develop ML/AI/CV roadmap and educate both internal and external stakeholders at all levels to drive implementation and measurement.
• Hands on experience in Image processing for auto industry
• BFSI domain knowledge is a plus
• Provide thought leadership to enable ML/AI applications.
• Manage products priorities and ensure timely delivery.
• Develop and evangelize best practices for scoping, building, validating, deploying, and monitoring ML/AI products.
• Prepare and present ML modelling results and analytical insights that help drive the business to senior leadership.

The Essentials

• 8 + years of work experience in Machine Learning, AI and Data Science with a proven track record to drive innovation and business impacts
• 4 + years of managing a team of data scientists, ML and AI researchers and engineers
• Strong machine learning, deep learning, and statistical modelling expertise, such as causal inference modelling, ensembles, neural networks, reinforcement learning, NLP, and computer vision
• Advanced knowledge of SQL and experience with big data platform (AWS, Snowflake, Spark, Google Cloud etc.)
• Proficiency in machine learning and deep learning languages and platforms (Python, R, TensorFlow, Keras, PyTorch, MXNet etc.)
• Experience in deploying machine learning algorithms and advanced modelling solutions
• Experience in developing advanced analytics and ML infrastructure and system
• Self-starter and self-motivated with the proven ability to deliver results in a fast-paced, high-energy environment
• Strong communication skills and the ability to explain complex analysis and algorithms to non-technical audience
• Works effectively cross functional teams to build trusted partnership
• Working experience in digital media and entertainment industry preferred
• Experience with Agile methodologies preferred

• Act as a lead analyst on various data analytics projects aiding strategic decision making for Fortune 500 / FTSE 100 companies, Blue Chip Consulting Firms and Global Financial Services companies • Understand the client objectives, and work with the PL to design the analytical solution/framework. Be able to translate the client objectives / analytical plan into clear deliverables with associated priorities and constraints • Collect/Organize/Prepare/Manage data for the analysis and conduct quality checks • Use and implement basic and advanced statistical techniques like frequencies, cross-tabs, correlation, Regression, Decision Trees, Cluster Analysis, etc. to identify key actionable insights from the data • Develop complete sections of final client report in Power Point. Identify trends and evaluate insights in terms of logic and reasoning, and be able to succinctly present them in terms of an executive summary/taglines • Conduct sanity checks of the analysis output based on reasoning and common sense, and be able to do a rigorous self QC, as well as of the work assigned to analysts to ensure an error free output • Aid in decision making related to client management, and also be able to take client calls relatively independently • Support the project leads in managing small teams of 2-3 analysts, independently set targets and communicate to team members • Discuss queries/certain sections of deliverable report over client calls or video conferences Technical Skills: • Hands on experience of one or more statistical tools such as SAS, R and Python • Working knowledge or experience in using SQL Server (or other RDBMS tools) would be an advantage Work Experience: • 2-4 years of relevant experience in Marketing Analytics / MR. • Experience in managing, cleaning and analysis of large datasets using statistical packages like SAS, R, Python, etc. • Experience in data management using SQL queries on tools like Access/ SQL Server

freshers of Bigdata, Data scientist, Computer vision of their skills